(1) Field of the Invention
This invention relates to a method of comparing the effectiveness of preventive care programs for chronic patients using a metric for performance that can then be illustrated via the use of a “Preventive Care Atlas™” and scatter plots of care performance and Costs. More specifically this invention relates to the creation of a new cost model for a population, with chronic disease as the designated risk, so as to calculate trends in incidence, prevalence and severity of chronic conditions in a population and estimate the associated impact on healthcare costs.
(2) Description of Related Art
General description of the historical problem: Healthcare costs have been rising, mostly because more people have become chronically ill, and there is an increasing realization that until we can lower medical needs by keeping people healthy the trend will continue unabated. There is also the fear that preventive care programs designed to keep chronic people healthy can be expensive and employers need to see a return on their investment before financial managers in businesses will offer their unreserved support. But to identify the beneficial effects of a preventive care program on an individual may take many years and employers are reluctant to invest today for what can only become visible many years hence. Clearly what is needed is a method to help employers measure cost and savings arising from preventive care programs.
Businesses use models as laboratories. Pricing models can be used to understand market forces of demand and supply. Cost models help companies budget their resources and manage costs. Without good models businesses will find themselves financially adrift using trial and error instead of getting actionable guidance from models.
Healthcare is no exception in the use of models to guide business decisions and there are many popular examples. Analysis of prior claims data is used to model utilization and negotiate favorable payment rates to specialists and labs. HMOs used the concept of “prepaid” models to transfer their risk to primary care physicians. To bring uniformity to treatment Medicare has used a DRG (Diagnosis Related Group) model to bundle hospital services and healthplans have paid based on models defining “episodes of care” rather than for individual office visits and procedures.
But the basic cost model in healthcare was designed for underwriting insurance premiums and actuaries used the same risk factors that life insurers have used—age and sex of an individual. Two or more decades ago it was possible to explain annual rising costs as being due to the aging of the employee population, the assumption being older people have more medical needs and so incur more costs. But that is not the case any more.
There are two problems with using age and sex to explain rising costs in a population. First, claims data from sample populations clearly establishes that aging cannot be the sole reason because annual cost increases appear in many age segments not just in the oldest ones. Second, this is giving rise to a negative psychological effect that is hurting reform efforts in the market. If rise in costs are due to the natural process of aging, as it is argued, then, short of rejuvenation, there is nothing much that can be done. This results in financial managers of companies being helplessly sidelined as they watch annual healthcare costs rise unabated.
That is not to say that actuaries have not recognized the need for taking into account the chronic illness of an enrollee in determining premiums. In fact current cost models assign a statistical probability for acquiring a chronic illness or developing complications and it is part of a “burden” associated with the person. But to get the results for a population it will then be necessary to multiply the various individual probabilities and thus introduce a very large number of adjustable variables. This challenges “parsimony”, i.e., using the least number of variables, rendering many of the predictions for populations of questionable value.
To put it another way, there is not a “cost model” that adequately accounts and measures the temporal development of disease and costs of a population. Without such measurements, comparisons are not quantitative but qualitative, and judgment of effectiveness and performance of preventive care programs remain vague.